개발 스킬

Configure and troubleshoot Apache Beam runners, the engines that execute data processing pipelines. Covers local testing, Dataflow, Flink, and Spark, with Java and Python examples, runner validation tests, and guidance on logs and execution settings.

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• Test a Beam pipeline locally
• Configure pipeline execution on Dataflow
• Review Flink or Spark execution settings

Develop and verify changes to Apache Beam's Python SDK. Set up a virtual environment, run tests, build installable packages or containers, and run data processing pipelines with the modified SDK.

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• Set up an Apache Beam Python SDK development environment
• Run unit and integration tests for SDK changes
• Build SDK packages and container images

Learn Apache Beam's core concepts through Java and Python examples. Understand distributed datasets, processing steps, pipeline execution, and time windows, with guidance on aggregation, late data, error handling, and sharing processing steps across languages.

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• Learn how Pipeline, PCollection, and PTransform fit together
• Understand grouping, aggregation, merging, and splitting
• Study time windows, output timing, and late data

Build Apache Beam connectors that read and write external data. This guide covers Java implementation, schema support for structured records, access from Python and Go, Managed API integration, and testing.

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• Add a connector for an external data system
• Make a Java connector available to Python and Go
• Integrate a connector with Beam YAML and the Managed API

Helps add Apache 2.0 license headers to new Apache Beam files using the correct comment format and placement. Covers source files, configuration, documentation, and local checks for missing license notices.

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• Adding license headers to new source and test files
• Checking license placement in YAML frontmatter
• Investigating missing headers with RAT

Build and test Apache Beam with Gradle, the system that manages its project tasks. Find relevant configuration files, inspect library dependencies, run formatting checks, publish locally, and investigate build failures.

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• Build or test a specific Apache Beam module
• Inspect library dependencies and version conflicts
• Run formatting and pre-commit checks

Guides adding metadata, extra information attached to data elements, to Apache Beam's WindowedValue. Maps the changes needed across serialization, storage, processing, and runner interfaces so new fields remain available during pipeline execution.

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• Adding trace context or drain flags to WindowedValue
• Checking metadata preservation through Windmill storage
• Reviewing propagation through grouping and timers

Develop and troubleshoot Apache Beam's YAML SDK. Understand its source files, run data processing pipelines locally or on Dataflow, test changes, and investigate provider issues or mismatched record fields.

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• Find source files for Beam YAML changes
• Run a YAML pipeline locally or on Dataflow
• Run unit tests and external service integration tests

Work with Apache Beam I/O connectors, components that read and write external data. Get guidance on connector usage, unit and integration tests, troubleshooting data connections, and the basic structure of new connectors.

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• Add BigQuery or Kafka reads and writes to a pipeline
• Run unit and integration tests for connectors
• Investigate data source or destination issues

Navigate Apache Beam contributions from finding an issue to submitting a pull request, a proposed code change, and responding to reviews. Covers environment setup, tests, formatting, licensing requirements, and closer evaluation of changes to core components.

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• Prepare a first Apache Beam contribution
• Organize a pull request and its related issue
• Check tests and formatting before submission

Review release notes stored in changeset files before a release. Check that entries describe user-facing changes, group related updates, remove unnecessary implementation details, and commit the resulting edits.

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• Reviewing changeset files before a release
• Grouping related changes into one release note
• Rewriting technical notes for users

Package a website URL as a desktop application for macOS, Windows, or Linux using pake-cli. Customize its name, icon, window size, and advanced options, then receive the installer file and installation guidance.

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• Turn a frequently used website into a desktop app
• Customize an app’s icon and window size
• Create an installer for the target platform

Understand software architecture, trace request flows, and assess the impact of code changes using Ontoly’s graph of software relationships. Answers include supporting graph evidence, confidence, and relevant limitations.

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• Explain a repository’s architecture
• Trace requests through routes and services
• Assess dependencies before refactoring

Build a new agent skill from a structured template. Copy the directory and edit SKILL.md to document its purpose, inputs, outputs, processing steps, precautions, and examples, replacing placeholders with concrete content.

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• Draft the documentation for a new agent skill
• Define a skill's inputs and output format
• Organize processing steps and precautions

Save a rendered web application view as static HTML with embedded styles and images. Capture a specific page or interface state for sharing or Stitch upload, using Puppeteer or an interactive browser capture workflow.

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• Share a page as static HTML
• Prepare a screen for Stitch upload
• Capture a view after clicks or form input

Find, install, and customize shadcn/ui components for React applications. The skill guides project setup, theme changes, forms, dialogs, and dashboard layouts, with checks for keyboard access, screen reader support, and responsive behavior.

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• Add UI components to an existing React project
• Customize themes and component variants
• Build forms and dashboard layouts

Turn Stitch designs into React and Vite dashboards with reusable components and asynchronous data fetching. It applies shared design settings from DESIGN.md, includes accessibility checks, and supports optional blockchain data reads.

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• Build a React dashboard from a Stitch screen
• Apply shared design settings from DESIGN.md
• Add data fetching and loading states

Turn Stitch HTML designs into React Native screens and reusable components, or update existing components to match newer designs. Extract shared style values, implement layouts with StyleSheet, and organize navigation, data, and interaction logic.

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• Convert Stitch designs into React Native screens
• Update existing components to match newer Stitch designs
• Share colors, fonts, and spacing across screens

Turn Stitch designs into reusable React components for Vite projects, or update existing components to match revised designs. Organize interface elements, logic, and data separately while aligning styles and connecting navigation between pages.

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• Build React screens from Stitch designs
• Update existing screens after design changes
• Split repeated interface elements into reusable components

Build a website one page at a time with Stitch. Each round reads a task file, generates and integrates a page, updates the site plan, and leaves instructions for the next round.

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• Build a site with several pages in repeated rounds
• Keep new pages aligned with a shared design guide
• Add pages following a site roadmap

Manage Apps Script projects through gog: inspect code and metadata, list versions and deployments, download projects locally, create new projects, and run deployed functions with explicit account selection and checks before changes.

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• Inspect Apps Script project code and metadata
• Download a project to a local directory
• Check project versions and deployments

Prepare a separate Git working directory for feature development, then install project dependencies and run baseline tests. Check for existing isolation first, use native worktree tools when available, and otherwise fall back to Git.

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• Starting feature development in a separate working directory
• Preparing a workspace before executing an implementation plan
• Reusing an existing isolated workspace

Investigate bugs, failing tests, and unexpected behavior through reproducible steps, logs, and comparisons with working code. Follow four stages to identify the root cause, test a hypothesis, apply a focused fix, and verify the result.

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• Investigating failing tests
• Tracing production bugs to their source
• Finding where a build or integration breaks

Standardize Chinese Git commit messages and changelogs using Conventional Commits, a structured message format. The skill provides writing rules and configuration examples for message checks, interactive commit entry, and automatic changelog generation.

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• Standardizing Chinese commit messages across a team
• Checking commit formats with commitlint and husky
• Generating changelogs with Chinese section headings